(a) Field of the Invention
The present invention relates to a biometric figure recognition system and method using a watch list, for performing adaptive figure recognition in consideration of figure features provided in the watch list, and detecting and tracking a subject such as a face in a complex scene in a place where a great volume of people gather together.
(b) Description of the Related Art
Regarding security systems including the well-known biometric system, the methods and systems for acquiring security include the following skills so as to improve system precision, reliability, and adaptivity.                Ambush video observation        Detect persons in an observation area        Track subject movement        Adaptively select figure recognition methods for a predetermined watch list based on template image characteristic        
For example, the Russia Federation Application No. 2006118145 discloses a method for designing a figure detection system with adaptivity for a complex scene. It improves the productivity level of the face detection system and the adaptive level of the scene item difficulty, and enlarges application fields of the biometric figure identification system to scenes having high item difficulties. Also, the above-noted skill optimizes stability and detection speed according to the characteristic of predetermined scenes. A similarity coefficient with persons is estimated based on the image quality estimation method, which improves poor quality images and eliminates figures with a bad lighting state to thus improve the figure recognition level. However, the skill does not estimate the image quality in detail and has an insufficient adaptivity level for characteristics of a predetermined watch list.
Russia Federation Application No. 2006118146 discloses a method for integrating a camera and lighting automatic control so as to detect the subject, track the subject, estimate the image quality of the detected subject, restore the subject image using 3D scene remodeling, and improve the captured and processed subject image. The skill is image quality estimation according to parameter spectrum, image quality improvement, and figure recognition according to the image quality estimation. However, the skill does not provide a method for recognizing predetermined watch list characteristics.
U.S. Pat. No. 6,826,300 discloses a method for measuring proximity between a template image and a corresponding image. This method suggests substantial face image characteristics based on the Gabor wavelet standard. The method selects an important valid shape of the face image based on the PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) method, and estimates the proximity according to one of the Mahalanobis estimation and cosine estimation. However, the proximity estimation method does not consider data characteristics and is not adapted to the template image of the watch list.
U.S. Pat. No. 7,031,499 is a subject recognition system that recognizes a subject type from an image gallery based on a filter set and a divider amplification method, and hence cascade weights of dividers are adaptively generated and detection tasks for various subject types can be solved. However, the skill cannot adaptively select the recognition method according to the characteristics of a predetermined watch list.
The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.